Transnational Rebels. Neighboring States as Sanctuary for Rebel Groups

Transnational Rebels: Neighboring States as Sanctuary for RebelGroups

Salehyan, Idean.

World Politics, Volume 59, Number 2, January 2007, pp. 217-242 (Article)

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TRANSNATIONAL REBELSNeighboring States as Sanctuary for

Rebel GroupsBy IDEAN SALEHYAN*

DESPITE differences in political institutions and policies, all states claim a monopoly on the domestic use of legitimate force and all

seek to prevent armed challenges to their rule. While such a monopoly is rarely absolute, states generally enjoy a preponderance of military ca-pabilities and organization relative to domestic opponents. Yet despite this apparent strength as compared with nascent rebel groups, civil wars are quite common—indeed, they are much more common than inter-national wars—and societies marred by such violence suffer devastating effects. This presents an apparent puzzle for social scientists: Why are relatively weak rebels undeterred by much stronger states? Why does the state fail to maintain domestic order within its territory and among its people? These questions are especially perplexing given that many long-lived rebel organizations remain vastly weaker than their govern-ment opponents. Quite small insurgent groups in Myanmar and north-east India, for example, have evaded state repression for decades. Civil wars and insurgencies have usually been attributed to domestic factors. Income inequality, ethnic divisions, state instability and weak-ness, and natural resource dependence—among other issues—have been offered as factors motivating rebels or enabling conflict to emerge.1 Statistical analyses, moreover, frequently treat country observations as independent of one another. However, decades ago Theda Skocpol re-

* I would like to thank Kristian S. Gleditsch, Barbara F. Walter, David Lake, Wayne Cornelius, Gordon Hanson, Will H. Moore, Scott Gates, and David Cunningham for their comments and sug-gestions. I also thank the three anonymous reviewers and the editors at World Politics. A previous version of this article received the 2005 Carl Beck Award from the International Studies Association.

1 See Paul Collier and Anke Hoeffler, “Greed and Grievance in Civil War,” Oxford Economic Papers 56, no. 4 (2004); James D. Fearon and David D. Laitin, “Ethnicity, Insurgency, and Civil War,” Ameri-can Political Science Review 97, no. 1 (2003); Håvard Hegre, Tanja Ellingsen, Scott Gates, and Nils Petter Gleditsch, “Toward a Democratic Civil Peace? Democracy, Political Change, and Civil War, 1816–1992,” American Political Science Review 95 (2001); Marta Reynal-Querol, “Ethnicity, Political Systems and Civil Wars,” Journal of Conflict Resolution 46, no. 1 (2002); Barry Posen, “The Security Dilemma and Ethnic Conflict,” Survival 35, no. 1 (1993).

World Politics 59 ( January 2007), 217–42

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2 Theda Skocpol, States and Social Revolutions: A Comparative Analysis of France, Russia and China (New York: Cambridge University Press, 1979).

3 See, for example, Dylan Balch-Lindsay and Andrew J. Enterline, “Killing Time: The World Politics of Civil War Duration, 1820–1992,” International Studies Quarterly 44, no. 4 (2000); Daniel Byman, Deadly Connections: States That Sponsor Terrorism (Cambridge: Cambridge University Press, 2005); Daniel Byman, Peter Chalk, Bruce Hoffman, William Rosenan, and David Brannon, Trends in Outside Support for Insurgent Movements (Santa Monica, Calif.: Rand, 2001); Ibrahim Elbadawi and Nicholas Sambanis, “How Much War Will We See? Explaining the Prevalence of Civil War,” Journal of Conflict Resolution 46, no. 3 (2002); David A. Lake and Donald Rothchild, “Containing Fear: The Origins and Management of Ethnic Conflict,” International Security 21, no. 2 (1998); Kristian S. Gleditsch, All International Politics Is Local: The Diffusion of Conflict, Integration, and Democratization (Ann Arbor: University of Michigan Press, 2002); Manus Midlarsky, ed., The Internationalization of Communal Strife (New York: Routledge, 1992); Patrick M. Regan, Civil Wars and Foreign Pow-ers: Interventions and Intrastate Conflict (Ann Arbor: University of Michigan Press, 2000); Stephen M. Saideman, The Ties That Divide: Ethnic Politics, Foreign Policy, and International Conflict (New York: Columbia University Press, 2001); Idean Salehyan and Kristian S. Gleditsch, “Refugees and the Spread of Civil War,” International Organization 60, no. 2 (2006); Barbara F. Walter, Committing to Peace: The Successful Resolution of Civil Wars (Princeton: Princeton University Press, 2002).

4 But see Byman (fn. 3); Navin Bapat, “State Support for Insurgency and International Conflict” (Manuscript, Pennsylvania State University, 2007); idem, “State Bargaining with Transnational Ter-rorist Groups,” International Studies Quarterly 50, no. 2 (2006).

marked, “Transnational relations have contributed to the emergence of all social-revolutionary crises and have invariably helped to shape revolutionary struggles and outcomes.”2 Even a cursory look at several regions of conflict—for example, West Africa, the Caucasus, and Cen-tral America—reveals that international factors and external linkages are indeed important, validating Skocpol’s assertion. This article argues that the use of external sanctuaries is one of the most common strate-gies employed by rebel groups to evade state repression. Extensive data collection on rebel groups since 1945 indicates that a majority (55 per-cent) have used external bases to some extent. This finding alone casts considerable doubt upon analyses that treat states as self-contained units of analysis, ignoring their broader regional context. This article contributes to a growing literature on the international politics of civil war. In recent years scholars have been paying much more attention to the international dimensions of civil conflict.3 Ex-ternal interventions, peacekeeping, and war externalities have come to the fore as the study of conflict has permeated the traditional field divi-sion between comparative and international politics. Yet scholars have largely ignored the possibility that rebel groups, unlike their govern-ment counterparts, are often unconstrained by national boundaries.4

In this article I argue that external sanctuaries in neighboring coun-tries provide an important opportunity for rebel mobilization. Further, they complicate the underlying bargain between states and rebels by exacerbating informational problems and introducing new actors into the bargaining environment. I therefore integrate political opportunity

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5 For example, Charles Tilly, From Mobilization to Revolution (Reading, Mass.: Addison-Wesley, 1978).

6 James Fearon, “Rational Explanations for War,” International Organization 49, no. 3 (1995).7 Christopher K. Ansell and Giuseppe Di Palma, Restructuring Territoriality: Europe and the United

States Compared (Cambridge: Cambridge University Press, 2004); Miles Kahler and Barbara Walter, eds., Territoriality and Conflict in an Era of Globalization (Cambridge: Cambridge University Press, 2006); Friedrich Kratochwil, “Of Systems, Boundaries, and Territoriality: An Inquiry into the Forma-tion of the State System,” World Politics 39 (October 1986); John Gerard Ruggie, “Territorality and Beyond: Problematizing Modernity in International Relations,” International Organization 47, no. 1 (1993); Harvey Starr and Benjamin Most, “The Substance and Study of Borders in International Relations Research,” International Studies Quarterly 20, no. 4 (1976).

8 Max Weber, From Max Weber, ed. H. H. Gerth and C. W. Mills (New York: Galaxy, 1958), emphasis added.

theories of civil war5 with a bargaining framework.6 While states enjoy a relative advantage in the internal use of force, their power is largely confined to their own security jurisdiction, or sovereign territory. If rebel groups can use other territories as a base of operations, thereby escaping the jurisdiction and repressive capabilities of the state, they can significantly lower their own costs of fighting and gain bargaining leverage. Yet as a result, bargains between transnational rebels and the government are hampered because external resources are difficult for the state to observe, credible commitments are harder to secure, and host countries complicate negotiations. These theoretical arguments will be developed in Section I. In Sec-tion II, I describe the methods and variables used in the empirical anal-ysis. Specifically, I employ a time-series cross-sectional analysis of civil conflicts during the period 1951–99. Section III presents the results of this empirical analysis and assesses their substantive impact on conflict behavior. Results support the claim that regional factors and external bases significantly contribute to conflict. Section IV concludes.

I. STATE BOUNDARIES AND TRANSNATIONAL REBELS

State boundaries are perhaps the most fundamental international insti-tutions in the modern state system.7 Borders define where the authority of one state ends and where that of another state begins. According to Max Weber, the state is an entity that “claims the monopoly of the legitimate use of force within a given territory.”8 Thus, territoriality is an inherent property of modern states. Internally, states have the power and authority to establish rules of the political game, regulate opposi-tion activities, and suppress challengers to its dominance. States may also regulate which types of flows—finances, goods, people, and so on—may cross their borders. In short, international boundaries define the sovereign jurisdiction and geographic territory of modern states.

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There has been considerable debate as to how effective the norm of state sovereignty is, with some arguing that sovereignty places impor-tant constraints on state behavior9 and others arguing that sovereignty is given no more than lip service.10 With respect to state capacity to regulate flows across boundaries, some have claimed that in an increas-ingly globalized world the state is becoming less effective at maintaining control over its borders,11 while others doubt that there is a diminished role for states in regulating international economic activity.12 Much of the debate about globalization and the erosion of national boundar-ies focuses on economic flows while neglecting the politico-military function of borders. As international institutions, state boundaries are agreed upon or de facto lines of defense against foreign aggression and geo-graphic demarcations of political authority. Modern states have insisted upon clearly defined borders and have fortified their frontiers against the intrusion of foreign state agents.13

While global flows of goods, capital, information, and people have been more or less open depending on the period in question, the police and military forces of the state have always been relatively limited in their mobility; indeed, some have argued that respect for the territorial integrity norm has increased in recent decades.14 In short, as no state welcomes military incursions across its borders, governments are likely to respond forcefully to such violations of their sovereignty. Respect for territorial integrity has also been affirmed through global institutions such as the United Nations system and regional agreements. This is to

9 Jeffery Herbst, “The Creation and Maintenance of National Boundaries in Africa,” Interna-tional Organization 43, no. 4 (1989); Robert H. Jackson, “Quasi-states, Dual Regimes, and Neoclas-sical Theory: International Jurisprudence and the Third World,” International Organization 41, no. 4 (1987).

10 Stephen Krasner, Sovereignty: Organized Hypocrisy (Princeton: Princeton University Press, 1999).

11 Joseph Camilleri and Jim Falk, The End of Sovereignty? The Politics of a Shrinking and Fragment-ing World (Brookfield, Vt.: Elgar, 1992); Wayne Cornelius, A. Takeyuki Tsuda, Philip Martin, and James Hollifield, eds., Controlling Immigration: A Global Perspective (Stanford, Calif.: Stanford Univer-sity Press, 2004); David J. Elkins, Beyond Sovereignty: Territory and Political Economy in the Twenty-first Century (Toronto: University of Toronto Press, 1995); Kenichi Ohmae, The Borderless World: Power and Strategy in the Interlinked Economy (New York: Harper Business, 1990).

12 Edward Cohen, “Globalization and the Boundaries of the State: A Framework for Analyzing the Changing Practice of Sovereignty,” Governance 14, no. 1 (2001); Peter Evans, “The Eclipse of the State: Reflections on Stateness in an Era of Globalization,” World Politics 50 (October 1997); John F. Helliwell, How Much Do National Borders Matter? (Washington, D.C.: Brookings Institution Press, 1998).

13 Peter Sahlins, Boundaries: The Making of France and Spain in the Pyrenees (Berkeley: University of California Press, 1989).

14 Peter Andreas, “Redrawing the Line: Borders and Security in the Twenty-first Century,” In-ternational Security 28, no. 2 (1998); Mark Zacher, “The Territorial Integrity Norm: International Boundaries and the Use of Force,” International Organization 55, no. 2 (2001).


imply not that military violations of sovereignty never occur, but rather that engaging in them can be very costly—often prohibitively so. Al-though powerful states do at times infringe upon the sovereignty of others militarily,15 such actions are certainly costly for the initiator as well as for the target, and most states do not have the ability to impose their will on others. This limitation on the coercive power of the state has important im-plications for the study of civil war. States respond to dissent through a variety of means, including imprisonment, torture, and mass killings aimed at eliminating and/or deterring subversive groups. For the most part, however, government agents are “caged” by international borders. They cannot easily exercise force outside of their national boundaries, as doing so would necessarily violate the sovereignty of others. States jealously guard their exclusive right to police their own security juris-diction, and they are likely to challenge cross-border incursions by the police and military forces of other states. Nevertheless, most prominent studies of civil war have ignored the role that state boundaries play in limiting government force. Political opportunity theories of rebellion emphasize state coercion as a critical element in the decision to rebel. Charles Tilly writes that “governmen-tal repression is uniquely important because governments specialize in the control of mobilization and collective action . . . to keep potential actors visible and tame.”16 While group grievances may be an impor-tant motivation for conflict, fear of repression limits collective action. Thus, many have argued that “semirepressive” regimes, difficult ter-rain, regime instability, and poor infrastructure limit the government’s coercive control over society and allow dissatisfied groups to launch an insurgency.17

Scholars have recently begun to analyze civil and international con-flict under a common framework that emphasizes bargaining among actors.18 These scholars argue that since armed conflict is costly, ac-

15 See Krasner (fn. 10).16 Tilly (fn. 5), 101.17 Fearon and Laitin (fn. 1); Hegre (fn. 1); Jeffrey Herbst, States and Power in Africa: Comparative

Lessons in Authority and Control (Princeton: Princeton University Press, 2000); idem, “African Mili-taries and Rebellion: The Political Economy of Threat and Combat Effectiveness,” Journal of Peace Research 41, no. 3 (2004); Edward N. Muller and Erich Weede; “Cross-National Variation in Political Violence: A Rational Action Approach,” Journal of Conflict Resolution 34, no. 4 (1990).

18 Fearon (fn. 6); James D. Fearon “Why Do Some Civil Wars Last So Much Longer than Others?” Journal of Peace Research 41, no. 3 (2004); David Lake, “International Relations Theory and Internal Conflict: Insights from the Interstices,” International Studies Review 5, no. 4 (2003); Robert Powell, In the Shadow of Power: States and Strategies in International Politics (Princeton: Princeton University Press, 1999); Monica Toft, The Geography of Ethnic Violence: Identity, Interests, and the Indivisibility of Territory (Princeton: Princeton University Press, 2003); Walter (fn. 3).

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tors should prefer a negotiated settlement over beginning or prolonging a war. Bargaining failure is more likely when poor information about actors’ capabilities and resolve make it difficult to find a suitable dis-tribution of benefits; when credible commitments to a peace deal are hard to make; and/or when issue indivisibilities exist. Civil wars are different from international wars in a fundamental way, however: states have standing armies and can credibly threaten to use force, whereas would-be rebels lack preexisting military capabilities. In short, rebels must mobilize a sufficient threat in order to extract a deal.19 This sug-gests that a political opportunity framework can complement bargain-ing theories of conflict. Opportunities to mobilize a rebel army open up a bargaining space by providing rebels bargaining power and by reduc-ing the probability of government victory. There is no reason to believe, however, that political opportunities for rebellion are entirely determined by domestic factors. Although the state is constrained by international borders, social actors—including migrant diasporas and opposition groups—often organize transnation-ally. This incongruence between territorial nation-states and mobile citizens suggests that transnational opposition groups can engage in activities that would normally be proscribed domestically.20 If rebel groups can use other territories as a base of operations, thereby escaping the jurisdiction of their own state, they can significantly lower the costs of insurgency and improve bargaining outcomes. Access to neighboring territory will be especially important for rebels, as proximity facilitates attacking the target state.21 Finding a host state is not without costs, as rebel groups dependent on foreign hosts sacrifice some decision-making autonomy for security. Nonetheless, by mobilizing abroad, rebels who lack sufficient domestic opportunities can secure a better bargain than they otherwise could.22 However, as will be argued later, external mobili-zation complicates the bargaining environment in important ways.

19 Rebel mobilization may itself be violent, as insurgent groups use force to capture resources, in-timidate civilian populations, and/or signal their strength and viability to constituents.

20 Transnational organizations have received a good deal of scholarly attention, although much of this research has neglected violent groups. See, for example, Donatella Della Porta and Sidney G. Tar-row, Transnational Protest and Global Activism (Lanham, Md.: Rowman and Littlefield, 2005); Mar-garet E. Keck and Kathryn Sikkink, Activists beyond Borders: Advocacy Networks in International Politics (Ithaca, N.Y.: Cornell University Press, 1998); Robert Keohane and Joseph Nye, eds., Transnational Relations and World Politics (Cambridge: Harvard University Press, 1972); Thomas Risse-Kappen, ed., Bringing Transnational Relations Back In: Non-State Actors, Domestic Structures, and International Insti-tutions (New York: Cambridge University Press, 1995).

21 Empirically, others have found a statistical relationship between the location of civil wars within countries and international borders. See Halvard Buhaug and Scott Gates, “The Geography of Civil War,” Journal of Peace Research 39, no. 4 (2002).

22 Navin Bapat, “The Internationalization of Terrorist Campaigns,” Conflict Management and Peace Science (forthcoming).


External bases are tactically desirable for rebels because the state is better able to conduct counterinsurgency operations at home than abroad. When transnational rebels (TNRs) operate from extraterrito-rial bases, the state’s costs for repressing them increase significantly. First, neighboring governments will not tolerate extensive cross-border forays, and thus rebels are not exposed to the full brunt of repression efforts. Limited strikes can and do occur across national boundar-ies—for example, Cambodian troops shelled Khmer Rouge positions in Thailand and Ugandan forces entered Sudan in pursuit of the Lord’s Resistance Army. In each of these examples, however, the government whose sovereignty had been violated strongly objected and responded by hardening its borders. Thus, crossing the border is costly because it risks a military confrontation with another state—rebel hosts enter into the bargain.23

Second, even if a state could extensively enter another’s territory and attempt to permanently rid it of TNRs, it would still bear significant governance costs in doing so.24 The invading state would have to take, hold, and police part (or all) of the other state’s soil. Two instances where this occurred demonstrate the significant costs of this strategy. Israel invaded Lebanon in 1982 after repeated PLO attacks across the border and held on to Lebanese territory for almost two decades, be-coming embattled with Lebanese resistance groups. Similarly, Rwanda, which invaded Eastern Congo after Hutu militias began to reorganize in refugee camps, became embroiled in a protracted conflict there. Both of these endeavors were extremely costly for the invading governments, which is why such examples are rare and were pursued by states that perceived a threat to their existence. Third, states are less familiar with the population and terrain in other countries than at home. Counterinsurgency operations are more difficult to conduct when state agents lack local knowledge. The abil-ity to gather reliable information on opposition activities is critical to successfully combating such groups.25 Finally, although it is unclear to what extent international norms factor into the foreign policies of

23 Several recent studies have begun to explore the relationship between external support for insur-gencies and conflict between states. In this regard, see Bapat (fn. 4, 2006); Kenneth Schultz, “War as an Enforcement Problem: Interstate Conflict over Rebel Support in Civil Wars” (Manuscript, Stan-ford University, 2007); Idean Salehyan, “No Shelter Here: Rebel Sanctuaries and International Con-flict,” Journal of Politics ( January 2008)

24 On governance costs, see David A. Lake. “Anarchy, Hierarchy, and the Variety of International Relations,” International Organization 50, no. 1 (1996)..

25 Nathan Leites and Charles Wolf, Jr., Rebellion and Authority: An Analytic Essay on Insurgent Conflicts (Chicago: Markham, 1970).

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governments,26 international norms and laws enshrine the principles of national sovereignty and territorial integrity. Violations of territorial sovereignty have been condemned in numerous UN Security Council resolutions. For instance, both Rwanda and Israel faced several UN resolutions condemning border violations when pursuing TNRs. Clearly, in these examples the invading states did not comply with the UN, but international opprobrium is not costless and may have some effect on state behavior, especially when coupled with concrete sanctions. Thus, although the extreme claim that borders are sacrosanct should be avoided, national boundaries significantly constrain state capacity to repress challengers and raise the costs of counterinsurgency.27 Sov-ereignty grants states an advantage in the domestic use of force, but it also confines that force to a given geographic area. Transnational rebels can therefore mobilize in relative safety and escape across the border to avoid the bulk of state security forces.

NEIGHBORING COUNTRY CONDITIONS

Under what conditions are rebels likely to find sanctuaries in other states? First, international migration and diaspora communities im-ply that not all politically relevant populations reside within the bor-ders of the state.28 Refugees often play significant roles in opposition movements, and refugee camps in neighbors frequently provide shel-ter, recruits, and resources to insurgents. Oppressive governments and political violence are likely to cause substantial migration outflows, par-ticularly to neighbors.29 Refugees exit the state because of a direct ex-perience of persecution or political violence and therefore have strong motivations to oppose their home regime.30 Refugees living in squalid

26 See Peter J. Katzenstein, The Culture of National Security Norms and Identity in World Politics (New York: Columbia University Press, 1996).

27 Indeed, Leites and Wolf (fn. 25) argue that cutting off external support approaches a necessary condition for counterinsurgency (p. 40).

28 Fiona Adamson, “Crossing Borders: International Migration and National Security,” Interna-tional Security 31, no. 1 (2006); Terrence Lyons, “Diasporas and Homeland Conflict,” in M. Kahler and B. F. Walter, eds., Territoriality and Conflict in an Era of Globalization (Cambridge: Cambridge Uni-versity Press, 2006); Yossi Shain and Aharon Barth, “Diasporas and International Relations Theory,” International Organization 57, no. 3 (2003).

29Christian Davenport, Will Moore, and Steven Poe, “Sometimes You Just Have to Leave: Do-mestic Threats and Refugee Movements, 1964–1989,” International Interactions 29, no. 1 (2003); Will Moore and Stephen Shellman, “Fear of Persecution: Forced Migration, 1952–1995,” Journal of Conflict Resolution 40, no. 5 (2004); Susanne Schmeidl, “Exploring the Causes of Forced Migration: A Pooled Time-Series Analysis, 1971–1990,” Social Science Quarterly 78, no. 2 (1997); Myron Weiner, “Bad Neighbors, Bad Neighborhoods: An Inquiry into the Causes of Refugee Flows,” International Security 21, no. 1 (1996).

30 Not all refugees flee because of government persecution. Situational refugees flee general conditions of violence in a country and do not necessarily have a stake in the conflict; see Sarah


camp conditions, moreover, have very low opportunity costs for joining rebel organizations; doing so may offer a better quality of life and sense of purpose. Refugee communities may continue to be active in their opposition to their home country even after having fled the state, as demonstrated in the large literature on “refugee warriors.”31

Second, rebels from a State A may use the territory of State B if State B is incapable of stopping them due to institutional weaknesses. It is often argued that weak and/or failed states are ready havens for violent transnational actors.32 Weak states simply lack the resources and capac-ity to rid their territory of what is viewed as another state’s problem. They face high opportunity costs—including the diversion of resources away from domestic policing—for combating foreign insurgents. These host governments may or may not sympathize with the TNR and may even cooperate with the target government in policing efforts. How-ever, security cooperation creates transaction costs and even weak states will strongly object to incursions by the military and police forces of others, increasing the costs of counterinsurgency. Finally, the territory of State B may be used by insurgents from State A if States A and B are hostile to one another. States may foment re-bellion and instability in their neighbors in order to undermine rival governments. In these cases, not only are TNRs tolerated on the host state’s territory but they may even be actively encouraged and assisted. Furthermore, when two states view each other as rivals, borders are likely to be “hardened,” such that even minor incursions by neighbors will be seen as provocative. Hosting rebel groups may provoke reprisal attacks, but rival hosts are often willing to bear such costs given the benefits of promoting instability in their enemies.33 As examples, after the Iran-Iraq War ended in 1988, both countries continued to provide safe haven and support to the other’s opposition groups, with Iran sup-porting the Supreme Council for the Islamic Revolution in Iraq and Iraq backing the Mujahedin-e-Khalq.

Kenyon Lischer, Dangerous Sanctuaries: Refugee Camps, Civil War, and the Dilemmas of Humanitarian Aid (Ithaca, N.Y.: Cornell University Press, 2005). However, a significant subset of any refugee outflow is likely to include people who have a direct grievance against the state.

31 Byman et al. (fn. 3); Lischer (fn. 30); Stephen J. Stedman and Fred Tanner, Refugee Manipula-tion: War, Politics, and the Abuse of Human Suffering (Washington, D.C.: Brookings Institution, 2003); Myron Weiner, “Security, Stability, and International Migration,” International Security 17, no. 3 (1992–93); Weiner (fn. 29); Aristide Zolberg, Astri Suhrke, and Sergio Aguayo, Escape from Violence: Conflict and the Refugee Crisis in the Developing World (New York: Oxford University Press, 1989).

32 Bapat (fn. 4, 2007); Robert H. Dorff, “Failed States after 9/11: What Did We Know and What Have We Learned,” International Studies Perspectives 6, no. 1 (2005).

33 See Bapat (fn. 4, 2007); Byman (fn. 3), 260–62.

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Thus, when states preserve good relations with their neighbors and can limit TNRs, opposition groups lack an important opportunity to mobilize. Furthermore, friendly and capable governments should also be able to effectively prevent the infiltration of refugee camps by militants. There-fore, the effect of refugees on conflict may depend on where refugees are located: camps are more likely to become militarized when hosts are unable or unwilling to prevent rebel activities.34 Thus, refugees in weak and/or rival states will be more likely to contribute to rebellion.

THE BARGAINING ENVIRONMENT

Bargaining theories of conflict emphasize the inability of actors to find suitable agreements short of war, particularly since fighting is costly. I have argued that political opportunities to mobilize an insurgency open up a bargaining space by providing rebels a credible threat and by mak-ing it more difficult for the government to prevail. External sanctuar-ies are a significant source of mobilization potential. Weak neighbors, rival neighbors, and refugee communities35 in which to mobilize can improve bargaining outcomes for rebels, but these factors are common knowledge to both parties. Actors should simply update their beliefs about the probability of victory and adjust their demands accordingly. Commonly known information should not lead to war, and once in-formation has been revealed on the battlefield after the outbreak of conflict, negotiations are more likely.36

Transnational rebellions complicate the negotiating environment, making it more difficult for actors to reach an acceptable settlement. First, TNRs introduce an important source of uncertainty because exter-nal rebel operations are beyond the scrutiny of the state. States devote significant resources to establishing domestic intelligence capabilities to monitor dissident activities. However, external rebel operations are difficult for states to monitor and verify because they are at a relative

34 Lischer (fn. 30).35 It is argued here that refugee camps are a source of recruits and bases for rebels. However, refu-

gees may themselves complicate the bargaining environment, and that may lead to longer conflicts. States must offer credible commitments to allow refugees to repatriate and reintegrate back in the home country. They must also promise not to violate human rights again in the future, which may be difficult. Special bargaining problems posed by refugee communities are not addressed in depth here but are left for future work. On strategic issues involving refugee repatriation, see Lester Zeager and Johnathan Bascom, “Strategic Behavior in Refugee Repatriation: A Game Theoretic Analysis,” Journal of Conflict Resolution 40, no. 3 (1996).

36 Darren Filson and Suzanne Werner, “A Bargaining Model of War and Peace: Anticipating the Onset, Duration, and Outcome of War,” American Journal of Political Science 46, no. 4 (2002); R. Har-rison Wagner, “Bargaining and War,” American Journal of Political Science 44, no. 3 (2000).


disadvantage in gathering information in unfamiliar areas outside of their jurisdiction.37 This inability to gather information has typically been seen as an obstacle to effective counterinsurgency rather than as an impediment to bargaining. Yet extraterritorial mobilization may lead to divergent expectations about the likely outcome of conflict because states cannot reliably gauge the rebel’s strength and make appropriate offers. Rebels may try to signal their strength to the government, but because they have an incentive to overstate their capabilities in order to win greater concessions, such information is unreliable.38 Thus, exter-nal mobilization leads to an information-poor environment that exac-erbates information problems and makes negotiating difficult. Second, external mobilization exacerbates commitment problems. For civil wars to end, combatants must credibly promise to lay down their arms and forgo future violence.39 Yet, just as it is difficult for states to gather reliable information about rebel mobilization, it is also diffi-cult to monitor and verify full compliance with demobilization efforts. After a peace agreement rebels can hide resources across the border and regroup in external sanctuaries so long as permissive conditions in other states persist; this allows rebels the opportunity to renege on a deal in the future. Offering concessions without being confident that the rebels will abide by their part of the bargain would leave the state worse off than continuing to fight. Thus, states may doubt the credibil-ity of rebel promises to comply fully with demobilization agreements when external sanctuaries are available. Third, transnational mobilization complicates the bargaining envi-ronment by introducing new actors: the rebel host state(s). Cunning-ham argues that additional parties to a conflict make bargaining more difficult by introducing a new set of preferences that must be satis-fied. Bapat argues that insurgent (or terrorist) groups face difficulties in making credible commitments because of incentives to renege on a deal.40 He formally demonstrates that for negotiations to hold, insur-gent hosts must offer credible commitments of their own to rein in rebels on their territory but may be unwilling or unable to provide nec-essary guarantees to target governments. These studies suggest that the bargaining environment becomes more complicated when additional

37 Byman (fn. 3), 70.38 Fearon (fn. 6).39 Walter (fn. 3).40 David Cunningham, “Veto Players and Civil War Duration,” American Journal of Political Science

50, no. 4 (2006); Bapat (fn. 4, 2006).

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actors are included; rebel hosts can block negotiations between com-batants and make bargaining more difficult. For empirical analyses, however, the information available to actors and the beliefs that they hold are nearly impossible to observe. This makes testing propositions about bargaining difficult. We are therefore left with observing background conditions rather than private infor-mation or beliefs about “credibility.” External conditions such as weak states, rivals, refugees, and foreign sanctuaries make bargaining failure more likely, and so when these conditions exist, the probability of ob-serving war should be higher. Anecdotally, ethnic Albanian rebels in Macedonia, who operated across the border in Kosovo, claimed a rebel force of sixteen thousand, although this number was impossible to sub-stantiate and other estimates were much lower,41 making it difficult to strike an appropriate deal. Nonetheless, a direct test of this assumption is unfortunately beyond the present analysis.

HYPOTHESES

As already noted, rather than observing the information available to ac-tors, we can observe broader environmental conditions that make con-flict more likely. I argued that refugees, interstate rivalries, and weak neighboring states were important for external rebel mobilization. I also argued that the effect of refugees on civil war may be conditional on their presence in weak and/or rival states. All of these conditions should affect both the probability of conflict onset and the duration of the conflict. Therefore, rather than treating conflict onset and continu-ation as separate research questions, following ElBadawi and Samba-nis,42 I look at the incidence of conflict. I postulate the following hypotheses:

H1 (rivalry). Rebellion is more likely to occur when the state is bor-dered by a rival state.

H2 (weak state). Rebellion is more likely to occur when the state is bordered by a weak state.

H3a (refugee diasporas). Rebellion is more likely to occur when there are refugees in neighboring states.

H3b (refugee location). Refugees are more likely to contribute to rebellion if they are located in weak and/or rival states.

41 Julie Kim, “Macedonia: Country Background and Recent Conflict,” CRS Report for Congress (Washington, D.C.: Congressional Research Service, 2001).

42 Elbadawi and Sambanis (fn. 3).


Additionally, a more direct way of estimating the effect of external rebel bases is to include data on their presence; these data are now available.43 But because external bases are clandestine in nature, we can only ob-serve their use once fighting is under way rather than prior to the onset of conflict. I therefore include a fourth hypothesis that is specific to conflict duration.

H4 (extraterritorial bases). Conflicts will endure longer if rebels have access to extraterritorial bases.

It is important to note that weak states, rival states, and refugee com-munities operate through the mechanism of providing fertile grounds for TNRs to emerge. Therefore, direct measures of extraterritorial bases are expected to outperform these factors in combined models of con-flict duration.

II. DATA AND METHODS

DEPENDENT VARIABLE

The data are a time-series cross-section of country-year observations from 1951 to 1999—the years for which reliable data were available. Rather than looking exclusively at onset or duration, this study exam-ines conflict incidence.44 The initial conditions that lead to war may also be associated with how long a war lasts; but if onset and continuation are driven by different processes, we want to know this as well. There-fore, the dependent variable in this study is conflict incidence, or spells of conflict, which is dichotomous and coded 1 for years in which a coun-try experienced a civil war or internal violence and 0 otherwise. Much of the literature has looked at the phenomenon of civil war, which is normally defined by a somewhat arbitrary classification of conflicts based upon the number of battle deaths (usually one thou-sand or more). This threshold is not based on any theoretical criteria and poses methodological problems.45 Rather than looking exclusively

43 David Cunningham, Kristian Gleditsch, and Idean Salehyan, “Dyadic Data on Civil War,” Data Project (Colchester, U.K., and Denton, Tex.: University of Essex and the University of North Texas, 2007).

44 Elbadawi and Sambanis (fn.3).45 A high threshold for classifying binary events has important methodological limitations when

using either a lagged dependent variable or counts of years at “peace.” With a threshold of one thousand deaths, an event that falls just short of the cutoff point would not be counted as a conflict and would be assumed to have no impact on the subsequent probability of violence. In practice, however, low-intensity conflicts are likely to be systematically associated with a higher likelihood of future large-scale conflict.

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at war, which is an imprecisely defined concept, this study examines smaller insurgencies along with full-blown civil war. There are no good theoretical reasons to expect low- and high-intensity conflicts to be driven by entirely different factors. The list of civil conflicts used here is drawn from the Uppsala/PRIO Armed Conflicts Dataset (hereafter U/PACD), developed by the De-partment of Peace and Conflict Research at Uppsala University and the International Peace Research Institute of Oslo (PRIO).46 Because of data limitations on the independent variables, the start date of the analysis is 1951, rather than the U/PACD start date of 1945. From these data, I eliminate all cases of coups or instances in which a faction of the mili-tary was listed as the opposition, because these are conceptually distinct from rebellions emerging from popular forces. I also consolidate spells of conflict in which there are three or fewer interim years of “peace” between parties fighting over the same incompatibility.47 In reality, al-though active fighting may have ceased, the underlying conflict has not been resolved.

INDEPENDENT VARIABLES

The first hypothesis is that countries which border rival states are more likely to experience internal armed conflict. To test this claim, a variable for interstate rivalry, created by William R. Thompson, was included.48 These data are based upon qualitative accounts, foreign policy histories, belligerent public statements, and acts of aggression between countries. The Thompson data set differs from other rivalry data sets in not re-quiring a minimum dispute duration; nor does it rely upon counts of open armed hostilities.49 The Rival NB indicator used here is a dichoto-mous variable coded 1 for country-years in which the state in question neighbors at least one state that is considered a rival (and 0 otherwise). This indicator is lagged because issues arising from the conflict itself may lead to international rivalries.50 Neighbors are defined as states

46 Nils Peter Gleditsch, Peter Wallensteen, Mikael Eriksson, Margareta Sollenberg, and Håvard Strand, “Armed Conflict 1946–2001: A New Dataset,” Journal of Peace Research 39, no. 5 (2002). I include all intrastate and internationalized intrastate disputes (type 3 and type 4 conflicts in U/PACD) that occur on a state’s territory.

47 Alternative approaches (five-year intervals and no consolidation) were also considered, but re-sults do not vary significantly.

48 Thompson, “Identifying Rivals and Rivalries in World Politics,” International Studies Quarterly 45, no. 4 (2001).

49 See Thompson (fn. 48) for details. I thank William Thompson for providing me with an elec-tronic version of this data set.

50 I thank an anonymous reviewer for pointing this out. Results do not change substantially when using contemporaneous values.


located within one hundred kilometers of the borders of the country in question, including strict contiguity based on the Gleditsch and Ward Minimum Distance Dataset.51 This practice ensures the inclusion of neighboring states that are not strictly contiguous but that are sepa-rated by short spans of water. The second hypothesis is that weak neighboring countries are more likely to be used as cover for transnational rebel groups. I use two mea-sures for state weakness. First, I include a dummy variable coded as 1 if the country in question borders (within one hundred kilometers) at least one state that is experiencing armed conflict as defined by the U/PACD and 0 otherwise (Civil war NB). When a neighboring country is undergoing a civil war, its government does not have full control over its territory and is institutionally weak. While others have found a relationship between neighboring and local war, the explanation for conflict clustering offered here is that civil wars in neighboring coun-tries expose security weaknesses and divert resources toward combating domestic insurgents, a situation that provides TNRs with opportunities to take up extraterritorial bases.52

As an alternative measure of state weakness, I use data on the neigh-boring countries’ GDP per capita from Gleditsch’s expanded GDP data.53 Countries that are wealthier overall are expected to have better com-munications, administration, police resources, and infrastructure that may in part be captured by GDP per capita.54 A dummy variable (Low GDP per capita NB) was included if the state in question borders at least one country that falls below the 10th percentile for GDP per capita for that year.55

Finally, this study will assess the role that refugees in neighboring states play in facilitating conflict in their home country. To do so, I in-clude data from the United Nations High Commissioner for Refugees Population Data Unit.56 These data contain dyadic entries for annual refugee stocks, listed by origin and destination countries. I take the sum

51 Kristian S. Gleditsch, and Michael D. Ward, “Measuring Space: A Minimum Distance Data-base,” Journal of Peace Research 38, no.6 (2001).

52 For an additional discussion of clustering, see Salehyan and Gleditsch (fn. 3). 53 Kristian Gleditsch, “Expanded Dyadic Trade and GDP Data, 1946–92,” Journal of Conflict Resolu-

tion 46, no. 5 (2002).54 Fearon and Laitin (fn. 1).55 Alternative measures indicating the GDP per capita of the poorest neighbor and the mean neigh-

borhood GDP were also used, but this did not significantly change the results.56 I thank Bela Hovy of the UNHCR for providing me with these data. However, the UNHCR does

not keep track of figures for Palestinian refugees. Therefore, these data are supplemented with figures from the United States Committee for Refugees and Immigrants. Palestinian refugees are counted as originating from the state of Israel.

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of all refugees from the country of observation in all neighboring states (Refugees in NB). The distribution of this variable is highly skewed as the vast majority of country-years have no refugees in neighbors, and the data have a long right tail, with countries such as Afghanistan and Mozambique having more than one million refugees in neighboring states. Furthermore, the effect of refugees is not expected to be strictly linear but diminishing with size. Therefore, the natural log of refugees is used. Clearly, there is endogeneity in the refugee indicator. Several statisti-cal studies have confirmed that refugees are a consequence of civil war,57 whereas the argument here is that refugees may also cause or exacerbate conflict. The “refugee warrior” phenomenon is documented in a large number of case studies, supporting the notion that conflict and refu-gees are mutually reinforcing. Yet for statistical analysis, this presents methodological challenges, as current refugees may be a consequence of conflict and the causal arrow may run in both directions. I correct for this by taking into account once-lagged values of the DV and lagging the refugee variable. This way, the effect of refugees at t-1 is estimated while controlling for the effect of conflict at t-1. Taking into account conflict at t-1 may not be sufficient. A con-flict may cause a significant number of refugees, fighting may cease for a few years, and it may then resume again for reasons unrelated to refugees but as a result of attributes of the past conflict. One solu-tion to this problem relates to how the dependent variable was coded, with lulls in fighting of three or fewer years being subsumed under the larger conflict. During these brief interim periods, there may be refu-gees in neighboring states at t-1 but no actual fighting during this pe-riod, which would show up as a positive “hit” in the regression if these years were coded as peaceful. In addition, a variable for Peace years—the number of years the country has been at peace58—is included. If there was a recent war that led to a significant number of refugees, this is ac-counted for. This method also corrects for duration-dependence in the dependent variable, as discussed below.59

57 Davenport, Moore, and Poe (fn. 29); Eric Neumayer, “Bogus Refugees? The Determinants of Asylum Migration to Western Europe, International Studies Quarterly 49, no. 3 (2005); Schmeidl (fn. 29).

58 Because conflict data are available from 1945, the count of peace years since 1945 is taken.59 Lagging refugees one year and including a peace years indicator presents a high hurdle and may

understate the effect of refugees if conflict and refugee militarization occur simultaneously or unfold quickly. In addition, civilian populations may anticipate future conflict and flee before fighting begins. Endogenous relationships are difficult to disentangle and will require finer temporal units and alterna-tive methodologies. This will be left for additional research.


Refugees are also expected to have a larger impact in certain coun-tries relative to others. Hypothesis 3b holds that refugees are most likely to contribute to conflict if they are located in weak and/or rival states. To test this possibility, I include a variable that distinguishes between (1) refugees in neighbors that are rivals and/or at civil war and (2) refu-gees in all other neighbors.60 One final variable, the presence of extra-territorial rebel bases, will be discussed below.

CONTROL VARIABLES

A number of domestic variables found to be important in other stud-ies of conflict are included as controls. These factors include wealth, population, regime type, and ethnic relations. To begin with, a variable is included for the country’s GDP per capita (logged), which has been shown to be a robust predictor of conflict.61 GDP data are taken from Gleditsch62 and are lagged one year. Second, a control for total Popula-tion (logged and lagged one year) is included. It may be the case that countries with larger populations are more difficult to govern because state security forces are stretched thin when they must monitor dissent among a large population. Third, some studies have demonstrated that regime type is an im-portant predictor of civil conflict. Democracies encourage nonviolent means of dissent while the most authoritarian regimes can effectively deter opposition; regimes falling in between (“anocracies”) are most violence prone.63 It is argued that there is a parabolic relationship be-tween continuous measures of democracy and conflict. Regime data come from the combined democracy-autocracy score from the Polity IV project.64 These widely used data are a 21-point scale ranging from most autocratic (–10) to the most democratic (+10) regimes.65 Because conflict is likely to affect regime type, I use lagged values of the Polity score. To test for the curvilinear effect of democracy, I include a squared Polity term. Finally, it has been argued that the ethnic composition of the country may be an important predictor of conflict, although there

60 In alternative models separate variables were created for refugees in rival states, civil war states, and all others. This analysis does not yield significant results, although there is a high degree of col-linearity among the variables.

61 Collier and Hoeffler (fn. 1); Fearon and Laitin (fn. 1).62 See Gleditsch (fn. 53).63 Hegre (fn. 1); Muller and Weede (fn. 17).64 Monty Marshall and Keith Jaggers, Polity IV Project: Political Regime Characteristics and Transi-

tions, 1800–2002 (College Park, Md.: Integrated Network for Societal Conflict Research, Center for International Development and Conflict Management, 2002), www.cidcm.umd.edu/inscr/polity.

65Countries with special indeterminate codes ( -88, -77, -66) are assigned a value of zero, according to the standard practice in the literature and the recommendation of the Polity project.

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is little agreement as to which measure is most appropriate. I will not engage in this debate at length here, although I include as a control the ethnolinguistic fractionalization (Ethnic Frac) index used by Fearon and Laitin.66

METHODS

The data are in time-series cross-sectional format with country-years as the units of observation and a binary dependent variable (BTSCS) indicating the presence or absence of conflict. Because observations are collected over time, it is important to correct for temporal dependence among units. To begin with, I employ a logit model with a lagged de-pendent variable (Conflict t-1) to account for serial autocorrelation and include country random effects to account for additional nonindepen-dence.67 Additionally, Beck et al. propose a model for analyzing this data structure: the transition model.68 We can think of spells of conflict as two different “transitions” in the data. The first is the transition from peace to conflict, and the second is the transition from conflict to peace. More formally, the transition model is given as a pair of logit equations taking on different lagged values of the dependent variable:

1 P(yi,t = 1|yi,t –1 = 0) = (1) 1+exp–(Xi,t β+δdy=0)

1 P(yi,t = 1|yi,t –1 = 1) = (2) 1+exp–(Xi,t γ+λdy=1)

Where X is a vector of independent variables, β are the parameters for conflict onset, γ are the parameters for continuation, and d is the num-ber of periods for which the dependent variable has taken the value of 0 or 1 up to the current period. In practice, two logit models are run with the sample being split into groups based upon the value of the lagged DV. The first model estimates the probability of a new conflict onset given that there was peace in the previous year; the second model estimates the probability of conflict

66 Fearon and Laitin (fn. 1).67 Elbadawi and Sambanis (fn. 3).68 Nathaniel Beck, David Epstein, Simon Jackman, and Sharyn O’Halloran, “Alternative Models

of Dynamics in Binary Time-Series Cross-Section Models: The Example of State Failure” (Paper pre-sented at the annual meeting of the Society for Political Methodology, Emory University, July 2001).


continuation given that there was conflict in the previous year. The tran-sition model allows for differences in the effect of the right-hand side variables based on whether onset or continuation is being estimated.69 The transition model also allows us to easily correct for duration de-pendence by including a count of war years and peace years, d, for the split sample (Peace [war] years).70

III. RESULTS

Table 1 reports the results from the empirical models. The random ef-fects logit model (model 1) and both cuts of the transition model are given side by side. First, hypothesis 1 regarding interstate rivalries is supported in the random effects model, which displays a positive and significant coefficient. However, in the transition model, Rival NB is sensitive to whether onset or continuation is being estimated. 71 For the onset cut, although the coefficient is positive, high p-values indicate that rivalry may not have a consistent effect on onset across the sample. For duration, the effect is also in the expected direction, and the p-value is somewhat lower, reaching significance at the .1 level. Thus, there is modest evidence that rivalry has an influence on conflict con-tinuation, with the results for onset being more indeterminate. Interna-tional rivals may choose to confront their enemies directly rather than support rebel groups. Therefore, there may not be a regular relationship between rivalries and conflict onset if states can substitute strategies. However, once a civil war has begun, international rivals may attempt to use the conflict to their advantage and hinder a settlement.

69 This approach is analogous to the dynamic probit used by Elbadawi and Sambanis (fn. 3), among others. In the dynamic probit model, a lagged dependent variable and interaction terms between each IV and the lagged DV are included on the right-hand side. A major advantage of the transition model is presentational. It is easier to interpret a sample broken into two different sets than it is to compare coefficients between interacted and noninteracted variables.

70 Nathaniel Beck, Jonathan N. Katz, and Richard M. Tucker, “Taking Time Seriously: Time-Series Cross-Section Analysis with a Binary Dependent Variable,” American Journal of Political Science 42, no. 4 (1998).

71 There is a debate in the statistics literature on the utility of using tests of statistical significance for apparent populations. Normally, significance testing is used to give a measure of how confident the analyst or reader can be that the relationship in the sample holds true for the population to which one is generalizing. In the current study nearly all country-years since 1945 are analyzed, so the sample size approaches the entire universe of cases that the theory addresses. In this case, then, standard errors are not used to understand true population parameters but rather are used to determine the consistency of the statistical relationship in the observed data. They reveal how often the expected (probabilistic) relationship between the DV and IV occurs in practice. For a discussion, see Richard A. Berk, Bruce Western, and Robert E. Weiss, “Statistical Inference for Apparent Populations,” Sociological Methodol-ogy 25 (1995); and Kenneth A. Bollen, “Apparent and Nonapparent Significance Tests,” Sociological Methodology 25 (1995).

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As for hypothesis 2, Low GDP NB—one indicator for a weak state—is not shown to have an important effect on conflict in either model. The other weak state indicator—civil war in a neighbor—is positive and significant in the random effects model. By contrast, the transi-tion model shows that civil wars in neighbors may be more related to conflict onset than to continuation, judging by p-values. Perhaps once fighting is under way, governments that face TNRs in a weak neighbor-

TABLE 1REGRESSION RESULTS, NEIGHBORING COUNTRY CONDITIONS, AND

CIVIL CONFLICT

1. Random Effects Logit 2. Transition Model

Coef. Coef. (β) Coef. (γ)

(Std. (Std. (Std. Err.) p-value Err.) p-value Err.) p-value

Rival NB (t–1) 0.359 0.037 0.090 0.345 0.348 0.081 (0.201) (0.227) (0.249) Low GDP per cap. NB –0.046 0.426 –0.150 0.294 –0.151 0.301 (0.244) (0.276) (0.289) Civil War NB 0.605 0.001 0.645 0.002 0.221 0.207 (0.192) (0.217) (0.270) Refugees in NB (t–1) 0.040 0.024 0.004 0.449 0.047 0.019 (0.020) (0.029) (0.022) Population (t–1) 0.219 0.002 0.244 0.000 0.013 0.446 (0.077) (0.068) (0.098) GDP per cap. (t–1) –0.205 0.070 –0.180 0.128 –0.291 0.055 (0.138) (0.158) (0.182) Polity (t–1) 0.022 0.065 0.015 0.200 0.036 0.028 (0.015) (0.018) (0.019) Polity Squared –0.009 0.002 –0.011 0.002 –0.002 0.304 (0.003) (0.004) (0.004) Ethnic Fractionalization 0.846 0.020 1.172 0.002 –0.135 0.378 (0.412) (0.403) (0.435) Conflict (t–1) 5.317 0.000 — — — (0.182) Peace (war) years — — –0.009 0.153 0.071 0.001 (0.009) (0.024) Constant –4.665 0.000 –4.717 0.001 3.587 0.024 (1.333) (1.366) (1.804) N 5896 4920 976 Wald Chi Squared 1072.83 71.50 24.55 P> Chi Squared 0.000 0.000 0.006 Rho 0.155* — —

* indicates .05 significance for Rho Robust standard errors reportedP-values are of one-tailed significance tests


ing country are better able to develop strategies for containing these groups, thereby shortening the conflict. In some cases, target govern-ments and neighboring countries may develop common responses to their security problems and buildups of military forces along the border may not be as threatening. The possibility of security cooperation de-serves further research. Nonetheless, there is evidence to suggest that weak neighboring states do contribute to war. Finally, the random effects model demonstrates support for the refu-gee hypothesis (H3). In comparison, the transition model suggests that refugees have a positive and significant effect on conflict continuation and a less consistent effect on conflict onset. The lack of a significant result for the onset model is perhaps not surprising, given that in many cases conflict precedes large refugee flows and that steps to limit endo-geneity present a hard test. Refugees may be associated with new con-flicts, but it is difficult to disentangle the independent effect of refugees over prior war, which is accounted for by the peace years variable. How-ever, in support of hypothesis 3, refugees have an important impact on the prolongation of conflict. Of the controls, population has a strong effect on conflict onset but does not explain conflict continuation very well. Furthermore, higher GDP per capita is associated with a lower incidence of conflict across the models. When tested jointly (in likelihood ratio tests), the models find a parabolic relationship between conflict and the Polity index, with the most authoritarian and the most democratic countries experiencing less conflict. Ethnic fractionalization, however, appears to have a strong im-pact on conflict onset only. Table 2 looks in depth at the effect of refugees and analyzes hypoth-esis 3b regarding the importance of refugee location. The results of the random effects logit are reported along with the continuation cut of the transition model (as refugees were shown to be a better predictor of conflict duration). As expected, model 3, the random effects model, demonstrates a positive and significant effect for refugees in rival and/or civil war neighbors. However, refugees in all other neighbors are also shown to have a significant effect on conflict incidence. The transition model (model 4) also demonstrates a significant effect for refugees in rival/weak neighbors while the variable for refugees in all other states loses its significance. Thus, there is evidence to suggest that while refu-gees exacerbate conflict, their effect may depend on their being present in unstable and hostile states. To interpret the results, predicted probabilities were computed us-ing hypothetical values of the independent variables, using the esti-mation results from model 2. Only the results for the main variables

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that were statistically significant at reasonable levels will be reported here. To create the baseline comparison group, all of the dichotomous IVs were set to 0, refugees and Polity were set to 0, and all of the con-tinuous variables were set at their means. For the onset cut, the peace years variable was set to 10, while for the continuation cut, war years was set to 1. For conflict onset, in the baseline hypothetical scenario a country is expected to have a 2.6 percent risk of a conflict. A civil war

TABLE 2THE IMPORTANCE OF REFUGEE LOCATION

3. Random Effects Logit 4. Transition Model

Coef. Coef. (γ)

(Std. Err.) p-value (Std. Err.) p-value

Ref. in Rival/CW NB (t–1) 0.035 0.075 0.056 0.047 (0.024) (0.034) Ref in non-Rival/CW NB (t–1) 0.035 0.094 0.023 0.252 (0.026) (0.034) Rival NB (t–1) 0.384 0.028 0.286 0.122 (0.201) (0.246) Civil War NB 0.559 0.002 0.169 0.254 (0.188) (0.256) Population (t–1) 0.208 0.003 0.027 0.389 (0.075) (0.097) GDP per cap. (t–1) –0.193 0.065 –0.231 0.074 (0.127) (0.160) Polity (t–1) 0.020 0.079 0.032 0.041 (0.015) (0.019) Polity Squared –0.008 0.003 –0.002 0.294 (0.003) (0.004) Ethnic Fractionalization 0.829 0.018 –0.009 0.492 (0.396) (0.427) Conflict (t–1) 5.320 0.000 — — (0.181) War Years — — 0.064 0.002 (0.022) Constant –4.718 0.000 2.918 0.038 (1.256) (1.638) N 6049 1007 Wald Chi Squared 1100.47 27.20 P> Chi Squared 0.000 0.002 Rho 0.142* —

* indicates .05 significance for RhoRobust standard errors reportedP-values are of one-tailed significance tests


in a neighboring country boosts this probability to 4.8 percent, for an 85 percent increase in the risk of violence. For conflict continuation, the effects of rivalry and refugees were analyzed. The probability of conflict continuation for the baseline category is 81 percent, indicating that conflicts are very likely to persist for a subsequent year. Holding the other variables constant and shifting the value of rivalry from 0 to 1 raises this probability to 86 percent, or a 6.2 percent increase in prob-abilities. For refugees, moving from 0 to 100,000 refugees in neighbors raises the probability of conflict to 88 percent, or a 9 percent increase in probabilities over the baseline.

EXTRATERRITORIAL BASES AND CONFLICT DURATION

Once fighting is under way, we can directly observe whether or not reb-els are fighting from foreign sanctuaries. Because data are only available after fighting occurs, only conflict duration can be estimated (hypoth-esis 4). Moreover, it is important to note that the external base variable is a direct measure of the presence of TNRs while the indicators for weak states, rivals, and refugees are indirect factors that are likely to be associated with TNRs. Therefore, since these neighborhood conditions are predictors of bases, in combined models we should see the external base variable outperform these other factors. Moreover, weak states, rivalries, civil wars, and so on may cluster geographically for a number of reasons that are not directly related to the presence of external bases; correlations may hold for reasons unrelated to the theory. This model presents a direct test of the strategic use of external bases. The conflicts in the U/PACD were examined to determine whether the rebels had a presence outside of the boundaries of the target state.72 A three-part variable (External Base) was developed and coded as follows: 0 = no extraterritorial presence; 1 = limited or sporadic use of external territory; 2 = extensive and sustained use of extraterritorial bases.73 Of the 291 rebel groups listed in the U/PACD a majority (55 percent) had at least some access to neighboring territory. Values of this variable were included for each country-year observation and changes in these values, although not common, were included. Alternative codings were also estimated by combining the 0 and 1 categories as well as by combining the 1 and 2 categories, but these variations did not affect the results. To

72 For details, see Cunningham, Gleditsch, and Salehyan (fn. 43).73 For methodological reasons, this variable was lagged. Because data on extraterritorial bases were

collected only for country-years where the value of the dependent variable equals 1 (that is, when there is a civil conflict), the model cannot be estimated with the variable itself because there is no variation on the DV. However, including lagged values of the extraterritorial bases variable eliminates this prob-lem, and lagged values are very highly correlated with current values: R=.95.

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estimate conflict duration, the continuation cut of the transition model is used. As Table 3 shows, the effect of extraterritorial bases on conflict dura-tion is positive and significant. Substantively, the effect is large as well. Setting continuous variables at their means, war years to 1, and chang-ing the value of extraterritorial bases from 0 to 1 is predicted to increase the probability of war continuation by 12 percent over the baseline (from 82 percent to 92 percent). Changing the value of extraterritorial

TABLE 3EXTRATERRITORIAL BASES AND CONFLICT DURATION

Model 5 Model 6

Coef. (γ) Coef. (γ)

(Std. Err.) p-value (Std. Err.) p-value

External Base 0.903 0.000 0.881 0.000 (0.158) (0.164) Rival NB(t–1) — — 0.291 0.125 (0.253) Civil War NB(t–1) — — 0.177 0.255 (0.269) Refugees in NB (t–1) — — 0.029 0.114 (0.024) Population (t–1) 0.049 0.299 0.073 0.222 (0.093) (0.095) GDP per cap. (t–1) –0.382 0.008 –0.335 0.022 (0.157) (0.165) Polity (t–1) 0.034 0.037 0.039 0.019 (0.019) (0.019) Polity Squared –0.004 0.175 –0.004 0.178 (0.004) (0.004) Ethnic Fractionalization –0.374 0.204 –0.355 0.215 (0.452) (0.449) War Years 0.048 0.016 0.039 0.040 (0.022) (0.022) Constant 3.959 0.005 3.060 0.036 (1.524) (1.698) N 1007 1007 Wald Chi Squared 44.69 47.86 P> Chi Squared 0.000 0.000

* indicates .05 significance for RhoRobust standard errors reportedP-values are of one-tailed significance tests


bases from 0 to 2 increases the probability of war continuation by 17 percent (that is, up to a 96 percent predicted probability). Thus, in both statistical and substantive terms, hypothesis 4 is confirmed. In model 6 the neighborhood variables for rivals, weak states, and refugees are included along with the external base indicator. As ex-pected, the effects of these factors are swamped by the effect of the external base variable and the magnitudes of the coefficients are re-duced (compared with the models above), supporting the claim that these variables work through external bases.74 In diagnostic models not shown,75 I run bivariate regressions using bases as the DV and rivals, refugees, and weak neighbors as the IVs. Each of these variables is found to be a positive and significant predictor of bases, confirming expecta-tions.

IV. CONCLUSION AND IMPLICATIONS

This article demonstrates that regional conditions are important for understanding how civil wars unfold. Theoretically, rather than treating states in isolation, analysts should consider the neighborhood in which states are located and how international processes affect domestic poli-tics. Moreover, interactions between states and transnational social ac-tors play an important role in shaping not only antiregime violence but a whole array of social phenomenon. Thus, scholars should play much more attention to this incongruence between “states” and “soci-eties.” This article argues that weak states, rival states, and refugees in neighbors contribute to the emergence of TNR organizations, bargain-ing failure, and civil conflict. Each of these factors finds support in the regression results, and the transition model shows interesting differ-ences between conflict onset and duration. Most importantly, access to external bases was shown to have a significant effect on the prolonga-tion of conflict. Nevertheless, the empirical analysis presented here is admittedly limited, as the proposed bargaining dynamics are not tested explicitly. Further research into bargaining processes is needed. In ad-dition, more research should be devoted to the contagion of violence across regions and to the presence of zones of conflict where civil and international wars are mutually reinforcing. This study also has important practical implications. National bound-aries place fundamental limitations on the state’s ability to repress trans-

74 The three coefficients fail to reach joint significance in a likelihood ratio test: p>chi-squared = .15

75 Results are available from the author.

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national challengers. Despite being vastly weaker, violent transnational groups can even frustrate the world’s preeminent power, the United States. Notably, U.S. counterinsurgency operations in Afghanistan and Iraq have been hampered by the ability of opposition groups to slip across porous borders. After the invasion of Afghanistan, for instance, Taliban and al-Qaeda forces found sanctuaries in remote tribal regions of Pakistan, where the state has only limited control. Current conflicts in Darfur and Chad also cross national boundaries and are clearly in-terdependent. Hosting rebel groups and cross-border violence threaten relations between neighbors and can escalate into international crises. This suggests that states cannot effectively counter cross-border groups through unilateral military means but must cooperate with others to develop common strategies for combating transnational violence.

Documents

Transnational Rebels. Neighboring States as Sanctuary for Rebel Groups